Grant Success Congratulations to the following for their success in their grant applications: Associate Prof Chua Han Bing (CELTEX RM220K) Process Modeling and Optimization of Composting of Empty Fruit Bunches (EFB) from Oil-palm for Development of High Quality Organic Compost Dr Ujjal Ghosh (FRGS RM80.5K) Fundamental Model Development for Water Gas Shift Membrane Reactor for Greenhouse Gas Capture from Pre-combustion Processes. Dr Perumal Kumar (ERGS RM53K) Studies on the effect of viscoelasticity on the heat transfer performance of Al2O3 – water nanofluid in circular and noncircular ducts Dr Leblouba Moussa (ERGS RM50K) Innovative Vibration Isolation Systems for Equipments and Structures July 2012 School of Engineering & Science In this issue Intelligent biomechanical vision system – MUSCLE motion P.3 Origami and its Applications in Automotive Field P.5 Empowered Consumer’s Demand Side Response in Electricity Market P.7 Nonlinear Model for Lead-Rubber Bearing Isolator P.9 The Unusual Stalagmites of the Niah Caves P.10 Effect of Aeration Rate and Stirrer Speed on Micro-Aerobic Batch Fermentation Process P.12 Growth of TiO 2 -ZrO 2 Binary Oxide Electrode with Henna Leaves for Dye- Sensitized Solar Cell Application P.14 The July issue of R&D focus features articles from the interdisciplinary research groups within the School of Engineering & Science (SOES). The breadth of the articles covers the four multidisciplinary research groups, namely, the Energy and Environment Group, the Intelligent Systems and Design Group (ISD), the Peat and Structures Group and the Materials, Mechanics and Manufacturing Group. We also highlight some of the research areas in the ISD research group. Enjoy reading! 1 Editors: R&D Committee Internal Funding Opportunities •Curtin Sarawak Research Fund (CSRF) •Curtin Sarawak Research Clusters Fund (CSRCF) •Curtin Sarawak Collaborative Research Scheme (CSCR) •Curtin Sarawak Academic Grant "The great university ... should look ever forward; for it the past should be but a preparation for the greater days to be". John Curtin R&D f cus ISD Research Group The Intelligent Systems & Design (ISD) is one of the four research groups in SOES. It is a multidisciplinary research group, which focuses on: • Multi-scale Control • Control System Modelling • Complex System Design • Signal Processing • Integrated Energy System See page 2 for details ISD adopts Modelling, Optimization & Control Theories in the creation of optimal solutions to complex problems of practical importance to the society
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Grant SuccessCongratulations to the following for their success in
their grant applications:
Associate Prof Chua Han Bing (CELTEX RM220K)
Process Modeling and Optimization of Composting of
Empty Fruit Bunches (EFB) from Oil-palm for
Development of High Quality Organic Compost
Dr Ujjal Ghosh (FRGS RM80.5K)
Fundamental Model Development for Water Gas Shift
Membrane Reactor for Greenhouse Gas Capture from
Pre-combustion Processes.
Dr Perumal Kumar (ERGS RM53K)
Studies on the effect of viscoelasticity on the heat
transfer performance of Al2O3 – water nanofluid in
circular and noncircular ducts
Dr Leblouba Moussa (ERGS RM50K)
Innovative Vibration Isolation Systems for Equipments
and Structures
July 2012
School of Engineering & Science
In this issue
Intelligent biomechanical vision system – MUSCLE motion P.3
Origami and its Applications in Automotive Field P.5
Empowered Consumer’s Demand Side Response in Electricity Market P.7
Nonlinear Model for Lead-Rubber Bearing Isolator P.9
The Unusual Stalagmites of the Niah Caves P.10
Effect of Aeration Rate and Stirrer Speed on Micro-Aerobic Batch
Fermentation Process P.12
Growth of TiO2-ZrO2 Binary Oxide Electrode with Henna Leaves for Dye-
Sensitized Solar Cell Application P.14
The July issue of R&D focus features articles from the interdisciplinary research groups within the School of
Engineering & Science (SOES). The breadth of the articles covers the four multidisciplinary research groups,
namely, the Energy and Environment Group, the Intelligent Systems and Design Group (ISD), the Peat and
Structures Group and the Materials, Mechanics and Manufacturing Group. We also highlight some of the research
areas in the ISD research group. Enjoy reading!
1
Editors: R&D Committee
Internal Funding Opportunities
•Curtin Sarawak Research Fund (CSRF)
•Curtin Sarawak Research Clusters Fund (CSRCF)
•Curtin Sarawak Collaborative Research Scheme
(CSCR)
•Curtin Sarawak Academic Grant
"The
grea
t univ
ersity
... sh
ould
look
ever
forwa
rd; fo
r it t
he pa
st sh
ould
be b
ut a
prepa
ratio
n for
the
grea
ter d
ays t
o be".
Joh
n C
urtin
R&Df cus
ISD Research Group
The Intelligent Systems & Design (ISD) is one of
the four research groups in SOES. It is a
multidisciplinary research group, which focuses
on:
• Multi-scale Control
• Control System Modelling
• Complex System Design
• Signal Processing
• Integrated Energy System
See page 2 for details
ISDadopts
Modelling,
Optimization &
Control Theories
in the
creation of optimal
solutions
to complex problems
of practical
importance to
the society
2
The Intelligent Systems & Design Group
ISDadopts
Modelling,
Optimization &
Control Theories
in the
creation of optimal
solutions
to complex problems
of practical
importance to
the society
Signal Processing
0
2000
4000
-60-50
-40-30
-20
-35
-30
-25
-20
-15
Frequency (Hz)
Su
pp
ressio
n (
dB
)
Distortion (dB)
=1
=0.5
=0
Top Left: Subband signal processing with filter banks. Top Right: Optimization of Microphone arrays – efficient frontier as functions of J1 (noise power) and J2
(distortion). Bottom: Proposed structure of spatio-temporal processing for distance speech recognition
Complex System Design
Top Left: Vinyl acetate plant design for resource conservation. Top Right: Integrated CO2 capture in coal-fired power plant. Bottom: Integrated proton exchange membrane fuel cell –fuel processor (PEMFC-FPS) system
Complex System Modelling
Top Left: Empirical modelling methodology for complex biosystem under limited experimental data. Bottom Left: Transformed fermentation kinetic parameter of S. cerevisiae vs. aeration (AR) and stirring speed (SS). Top Right: Metabolic fermentation pathway in S. cerevisiae yeast [1]. Bottom Right: Framework of multiscale modeling for bio-technological systems
Integrated Energy System
Left: Fully-integrated agro-biofuel-biomaterial-biopower cycle for sustainable technologies [2]. Bottom: Proposed topological integration of multi-energy sources (wind, solar, hydro and coal power plants)
References[1] M. Rizzi, M. Baltes, U. Theobald & M. Reuss. Biotechnol. & Bioeng. 55(4): 1997[2] A.J. Ragauskas et als. Science, 311: 2006
Top Left: Multiscale feedback control (MSC) scheme vs. LQG and PID. Top Right: Block diagram of generalized MSC scheme. Bottom Left: Multiscale control system employing multi-scale structure (MSC). Bottom Right: MSC vs. single-scale control structure (SSC)
Multi-Scale Control
Intelligent biomechanical vision system –MUSCLE motion
Alpha Agape Gopalai & Lim King Hann
4
Visual-based tracking system in rehabilitation provides a suitable platform for continuous monitoring of
patients in identifying and correcting gait related problems. Visual systems in human motion analysis can
be classified into two sub-categories: (1) visual marker tracking system, and (2) markerless tracking
system. Visual marker tracking system requires skilled knowledge for mounting visual markers on
subjects’ body and encumbers human motion. Therefore, markerless visual tracking system presents
itself as a great potential alternative in human motion analysis. However, this alternative faces several
critical challenges: (1) Segmentation of fast human motion without introducing significant amount of
noise, (2) Occlusion of region of interest due to rotation or overlapping regions, (3) Synchronization and
fusing of scenes from multiple cameras (multiview), in order to reduce the occurrences of occlusion, and
(4) Ability to correct/communicate errors or abnormalities in real-time, when observed. The study
proposes a Markerless Multiview System for Corrective Lower Extremity Motion (MUSCLE Motion), in
order to overcome the four identified challenges of markerless tracking systems. The MUSCLE Motion
consists of a markerless motion analysis system that provides reliable real-time motion capture system
and joint kinematic parameters. These data is processed using computerized artificial intelligence to aid
in real-time identification of gait asymmetries and abnormalities of ambulation patterns. The proposed
system is expected to perform at par or better than current sensing technologies (visual markers or
sensing methods). MUSCLE Motion will also include an intelligent bio-feedback module, enabling the
system to communicate detection of abnormalities and asymmetries to the subject in an effective
manner. Successful implementation of MUSCLE Motion will see changes in current rehabilitation
techniques. The incorporation of artificial intelligence and accurate automation of processes within the
system will cause rehabilitation routines to no longer be confined to a facility or limited by the availability
of specific professionals.
Figure 1: An overview of the MUSCLE motion detailing the integration of the various components that
are required
3
5
Biomechanics is a division of science which
provides sound and logical basis to evaluate
motion and stance of human beings. This field of
study allows for engineers and scientists to
understand the wide variety of human physical
movements, which are achieved by the human
neuromusculoskeletal system and can range from
walking to the skilful performance of a professional
athlete. In the past two decades, the knowledge of
biomechanics has been widely applied in clinical
rehabilitation by utilizing mechanisms or
techniques to correct abnormal motion behaviour
to achieve better or near ideal posture. In addition
to that, with the aid of rehabilitative mechanism,
improved posture may be gained enabling
individuals experiencing injuries or disabilities to
regain highest possible level of independence .
In rehabilitation routines, the movement of
patients have to be continuously monitored and
rectified to maintain correct forms of motion. The
real-time monitoring and rectification of the
undesired motion behaviours during initial
rehabilitation stages are crucial for the re-learning
of motor skills. This is because brain plasticity and
adaptation depends heavily on provided stimulation
(natural or external). With the development in
biomechanics, various methods and tools for
collecting dynamic and kinematic parameters of
human posture have emerged. In the past
decades, human motion tracking methods using
various types of methods have been intensively
studied to help understand the various
biomechanical aspects of human movement.
Generally, human motion tracking technologies can
be categorized in to two major categories: (1) non-
visual tracking system, and (2) visual-based
tracking system.
Non-visual tracking systems function by
employing sensory tools to collect dynamic and
kinematic parameters of human posture. This
method is popular due to its mobility, compactness,
and efficient processing signal characteristics.
Inertial Measurement Unit (IMU) sensors are
among the many kind of available sensing
technologies which are widely used for human
motion monitoring. IMUs consist mainly of
accelerometers and gyroscopes. These sensors
are attached to human body/joints to record
movement information such as velocity, orientation,
and gravitational forces. Signals are analyzed by
monitoring the signal characteristics and occurring
clusters. However, a non-visual approach would
require foreign objects (sensors) to be attached to
the human body. This could affect and influence
the natural response of patients’ gait patterns.
Furthermore, a system of this nature would also
require the presence of trained personnel to assist in
the attachment of sensing nodes (or a knowledge to
do such) on the human body – limiting its application
in the wider society.
Visual-based tracking system using cameras,
however, are widely used to improve accuracy in
position estimation. This system can be further
classified into two sub-categories: (1) visual marker
tracking system and (2) markerless tracking system.
Visual marker tracking systems or marker based
tracking systems utilize simple image processing
techniques to identify human motion with the aid of
identifiers/markers on the human body, to identify
location of joints. Therefore, the major drawback
when using the maker based approach is that
rotated joints or overlapping body parts with markers
cannot be detected, which leads to difficulties in
determining the joint parameters. Marker based
systems also require for a trained personnel (or a
knowledge to do such) to be involved when placing
the markers on the joints/limbs.
In view of the limitations of the current available
technologies, markerless visual tracking system is
currently an intensive exploratory research area.
Researchers are looking at methods to locate human
joints automatically and to analyze joint parameters
using computerized intelligence without the aid of
identifiers (markers). A successful implementation of
this objective will see the acquisition of patients’
natural motion data in environments comfortable and
familiar to them (in the comforts of their home), thus
allowing for improved identification of pathological
problems. With the decreasing cost of optical
sensors and increasing performance of
microcomputers, it is now possible for the processing
of high volumes of captured visual frames in real-
time. This is a vital element to the viability of a real-
time markerless video tracking approach.
This work proposes the use of an automated
markerless vision system for rehabilitation, using an
intelligent bio-feedback system as the means of
correcting and improving monitored postures.
Outputs (kinematic parameters) from the vision
system will be analysed further to determine the
quality of postures or presence of asymmetries. This
decision on posture quality will be made using a
designed artificial intelligent model and will trigger
the necessary bio-feedback modalities.
Figure 2:
Summary of
the proposed
system and
its
relationship
with the
various
proposed
sub-systems4
Origami and its Applications in Automotive
FieldSujan Debnath
5
1. INTRODUCTION
Origami is the art of folding originated from
Japan and has been commonly practiced
worldwide. Traditionally square papers are
folded into 2 or 3 dimensional figures as
resemblances of existing matters like birds,
mammals, trees, furniture etc. As the
application is being introduced to the
scientists and engineers, Origami has
become a useful tool in design and fabrication
of appliances. Till date the folding is no longer
being restricted to square papers. Many
industry applications use origami technique in
designing new products. The Eyeglass space
telescope as shown in Fig. 1 designed by
Robert Lang is a great example in merging
origami and engineering.
FIG.1 Eyeglass designed by Robert Lang
(adopted from origami-resource-center.com)
2. ORIGAMI SCIENCE: The Fundamentals
Origami originated as a trial-and-error art
design for making paper(s) to appear like
real object by folding them. Later on several
mathematical approaches were developed
to understand the phenomena on the paper
generated by the folding and also to
estimate the outlook of the origami (folded
paper)
Mathematical approaches for Origami, to
name a few, are Geometry, Topology
(explained by Thomas Hull [1]), Robert
Lang’s Tree Theorem [2] and Maekawa’s
String-to-beads method [3]. The Tree
Theorem approaches are surrounding three
main fundamentals: Huzita-Hatori axioms,
Kawasaki and Haga’s theorems. The
components of of Tree Theorem are
molecules and stick figure also referred as
tree graph (Fig. 2)
• Given two points P1 and P2, there is a
unique fold that passes through both of
them.
• Given two points P1 and P2, there is a
unique fold that places P1 onto P2.
• Given two lines l1 and l2, there is a fold
that places l1 onto l2.
• Given a point P1 and a line l1, there is a
fold that places P1 onto l2.
• Given two points P1 and P2 and a line l1,
there is a fold that places P1 onto l1 and
passes through P2
• Given two points P1 and P2, and two
lines l1 and l2, there is a fold that places
P1 onto l1 and P2 onto l2.
• Given one point P1 and two lines l1 and
l2, there is a fold that places P1 onto l1and is perpendicular to l2.
FIG. 3 Bases of folding methods (1) Cupboard, (2) Windmill,
(3) Water bomb, (4) Preliminary Fold (adopted from [2])
The notations of Origami have been
standardized by scientists, to name a few,
including Lang, Huffman, Clowes, Waltz,
Takeo Kanade, and Akira Yoshizawa [2] & [5].
In summary, the notations being widely used in
the Origami practice are made of lines, arrows,
and terms as illustrated in Fig. 4 and Fig. 5.
(1)
(4)(3)
(2)
The basic folding methods in the industry
are the Cupboard Base, Windmill Base,
Water bomb Base, and Preliminary Fold [5]
as illustrated in Fig. 3.
The Huzita-Hatori axioms consist of 7
axioms were improved by Humiaki Huzita
and finalized by Koshiro Hatori, Justin and
Robert Lang in 2001. The axioms [4] are:
FIG.2 Top projection of an origami provides a tree graph
(adopted from [2])
5
The focus on type of windshield in this article is
for standard motorcycle. It provides full
protection from flying debris and wind when the
motorcycle is moving forward.
There are mainly two types of wind shield for
motorcycle: one allows the rider to look through
the windshield while the other not. The types of
windshield are illustrated in Fig. 6. In this project,
the latter type is chosen due to its suitability for
warm climate [6] as it is in Malaysia. Also it is
because of the consideration of providing a
minimal disturbed view to the rider on the road.
FIG. 6 Types of motorcycle windshield (adopted from [6])
Weight (Material): In practice the two most
common materials for motorcycle
windshield are polycarbonate (Lexan) and
acrylic (Plexiglas) [6]. They are chosen due
to their great transparency degree, strength
of materials, and durability in molding the
plastic. With the application of Rigid
origami, the panels (pieces of
polycarbonate) selection would based on
the available thicknesses from the
manufacturer.
Optical Consideration: The windshield
should not be an obstacle to the visibility of
the rider on the road (e.g. the road mark
should not appear to be bent to the rider).
Transparent material is to be used with
suitable coating for sunlight filtration.
Folding Process: At this stage the design of
the windshield involves manual unfolding
and folding process. Miura fold is to be
considered before further design
modification is done using Tree Maker and
Rigid Origami.
Attach Method: It is proposed for the
unfolded windshield to be attached to the
Rack using firm clip-on method.
4. CONCLUSION AND FUTURE WORKS
This article has presented the findings on
Origami science which mainly focus on the
Robert Lang’s Tree Theorem, the
fundamentals, Rigid origami and one of its
applications. Beyond this paper are works on
detailed designing a foldable (and usable)
motorcycle windshield with all the studied
Origami fundamentals and aiding software.
REFERENCES
[1] Andersen, Eric M. Eric's Origami Page -
Origami and Mathematics. 2004.
[2] Lang, Robert J. "TreeMaker User Manual.
"Langorigami. 2004. www.langorigami.com
[3] Lang, Robert J. Origami Design Secrets -
Mathematical Methods for an Ancient Art.
Massachusetts: A K Peters Ltd, 2003.
[4] Barile, Margherita, & Margherita Barile.
"Kawasaki's Theorem." From MathWorld--A
Wolfram Web Resource, created by Eric W.
Weisstein.http://mathworld.wolfram.com/Kawasaki
Theorem.html
[5] Kanade, Takeo. "A Theory of Origami World."
Artificial Intelligence, 1980: 280-311
[6] Lawrence, Mark. Windshields. 2007.
http://www.calsci.com/motorcycleinfo/Fairing.html
FIG. 4 Terms used in a typical Origami folding
(adopted from [3])
FIG. 5 Types of lines used in Origami (adopted from [2])
Types of Wind Shield
Wind Shield Design Parameters
Height: For a windshield to be shorter than the
rider after installation, a methodology
introduced by Mark Lawrence [6] is used to
determine the dimension of the windshield for
this project. The desired dimensions of the
windshield are found to be 40cm x 60cm (width
x height). These dimensions have included the
mounting requirement.
3. WIND SHIELD DESIGN USING ORIGAMI: An
Ongoing Project
6
Empowered Consumer’s Demand Side
Response in Electricity Market Fouad Kamel
It is generally agreed that consumers, at the tail-
end of electricity market, inherently possess the
ability to moderate the market and avoid most of
the currently experienced problems occurring
mainly due to demand congestions. Those
congestions are mainly due to lack of
coordination among consumers as well as
between consumer and suppliers [1]. With
adequate information about basic economic and
technical market operating conditions, consumers
could be able to contribute alleviating demand
congestions and achieve enhanced economic
performance.
Under the smart grid, consumers will be an
integral part of the power system, where they are
encouraged to participate in system operation
and management. From the perspectives of
market operators controllable demand is another
resource; it will help balance supply and demand
to ensure system reliability and moderated
energy price.
The proposed scheme is acting upon publicly
available 30 minutes periodical information on
demand and price conditions released and
updated by the Australian Energy Market
Operator (AMEO) on the internet [2]. Figure 1
depicts an example of actual energy demand and
price conditions in Queensland. The price pattern
is closely following that of the demand. Electricity
price is typically at its lowest level during times of
low demand (off-peak) e.g. at night. Traditionally,
prices soar twice daily following morning and
evening peak demands.
1
Fig. 1: Wholesale electricity price in Queensland on 2nd - 4th May 2010 [2].
Introduction:
The proposed scheme comprises a technical set-
up of a programmable internet relay, a router,
solid state switches in addition to the suitable
software to control electricity demand at
consumer’s premises. The software on
appropriate multimedia (CD Rom) offers
consumers optimizing control of energy
consumption [3]. The relay is programmed to
receive and act upon information received about
electricity demand/price conditions every 30
minutes from the Australian Energy Market
Operator (AEMO) over the internet. The scheme
is presenting a low-cost DSR technique, which
assists electricity consumers to be shifting loads
around the clock averting peak-demand periods.
This shall help consumers to be engaged
mitigating peak demands on the electricity
network.
The scheme is primarily applicable for
commercial and industrial consumers on
fluctuating energy prices. For domestic
consumers on flat-rate tariffs, users are gaining
financial benefits from reducing energy
consumptions at certain times a day; mainly
averting peak-load periods. Domestic consumers
on different tariffs, where energy price differs with
day time and network conditions (e.g. night
tariffs) will be gaining financial benefits from
shifting loads from day- to night-times, when
electricity cost is lower. The scheme is expected
to be helping alleviating congestions on the
electrical network in Australian States covered by
the Australian Energy Market Operator (AEMO)
and other markets in similar operating condition.
Methodology:
7
8
[1] Kirschen D.S., Strbac G., Cumperayot P.,
and De Paiva Mendes D. (2000) "Factoring
the elasticity of demand in electricity prices"
in Power Systems IEEE 15 (2) pp. 612-617
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp
=&arnumber=867149
[2] Australia Energy Market Operator Current
Trading Interval Price and Demand Graph
Queensland. Retrieved from
http://www.aemo.com.au/data/GRAPH_30QL
D1.html
[3] Fouad Kamel and Marwan M. (2011)
"Smart Grid Techniques for Optimized
Energy Use" in Proc. Innovation in Power,
Control, and Optimization: Emerging Energy
Technologies, Pandian Vasant, Nadar
Barsoum and Webb J., Editors IGI Global:
Hershey USA.
Numerical example:
Fig. 2: Control Regime
Fig. 3: Occurrence of electrical energy demand in
Queensland during 2010 with average 5957 MW
The proposed DSR scheme aimed to develop
an integrated energy scheme that enables
electricity consumers to gain autonomous
control on own energy consumption securing
financial and energy savings to consumers.
The scheme is helping engaging consumers to
be participating in solving peak demand
congestions on the electrical network in
Australian States covered by the Australian
Energy Management Operator (AEMO) and
on other electricity markets in similar operating
conditions.
Conclusion:
To enable electricity consumers to control
electrical demand, a Demand Site Control Unit
(DSCU) and controllable switches are required.
Figure 2 depicts a DSCU controller [3]. Up to
date demand and price profiles are available
online on the Public Load Profile Web Server
(PLPW), in Australia the National Electricity
Market Operator (AMEO). The controller is
connected to the Internet and has access to the
PLPW. Many households and businesses have
broadband Internet connections. Wireless
broadband is also easily deployable at a low
cost when existing installations can not be used.
The DSCU controller is implemented in a simple
embedded router device commonly used in
home and office networks. This device connects
to the Internet as well as local appliance
switches via the home network. It controls the
appliance switches which in turn activate
appliances. At regular intervals, i.e. every 10
minutes, the control system downloads the
load/price information from the AEMO server
and evaluates the appliance profile. If
preconditions for appliances are met, power to
these units is turned on; if the cut off threshold is
reached devices are turned off.. Figure 2
illustrates the control regime, where e.g. three
appliances are controlled by three solid-state
switches receiving on/off signals from the relay.
Figure 3 depicts the case where the proposed
scheme is able to allow consumers to defer loads
from times of peak-demand to times of low-
demands. Such a procedure shall help flattening
the total energy demand to meet a constant
average of 5957 MW for Queensland, achieving a
plant utilization factor close to unity corresponding